Project Summary Despite progress in the field of human-machine interfaces to control assistive devices for individuals with tetraplegia, the learning burden to efficiently operate these devices rests largely upon their users. The objective of this proposal is to lessen this burden by leveraging principles of optimal control that govern unimpaired movement. Specifically, manipulating feedback noise may be an effective means of shaping and enhancing control of redundant degrees of freedom and may improve human-machine interface performance of individuals with tetraplegia. This work uses a kinematic human-machine interface that translates high dimensional body movements to low dimensional control commands. Clinical impact of the proposed work will be directly measured by conducting extensive assessments of individuals with tetraplegia performing functional tasks, controlling a computer cursor and driving a power wheelchair. The results of these studies are intended to inform training paradigms for a wide family of human-machine interfaces that exploit the availability to the disabled users of control signals in excess of the number of variables that are required to control an assistive device. If successful, this work will directly result in enhanced training paradigms for reorganizing human dexterity and adapting it to the constraints established by the disability. This will increase the number of individuals who will be able access assistive devices, increasing functional independence and broadly improving quality of life.